Headings of the journal
"Educational Resources and Technologies"

Annotation: The relevance of the topic is determined by the role and significance of teaching formal logic to students in social sciences and humanities. The object of the study is the theoretical and practical problems of teaching a general logic course in higher education. The subject of the study comprises the typical didactic and psychological difficulties that arise when mastering the core topics of the course: from operations with concepts and the analysis of judgments to the construction of inferences and argumentation. The aim of the study is to examine the causes of these difficulties, including the specific nature of humanistic thinking (polysemy, contextuality, reliance on content), as well as the gap between the abstract formalism of logical structures and real-life speech practices. The research methods include pedagogical observation, which allows for the identification of real difficulties in the learning process; content analysis of students’ work as a basis for verifying hypotheses about typical “weak points” in mastering the course; and analysis and synthesis of scientific literature aimed at collecting proven methodological solutions. The scientific novelty of the study lies in the fact that, based on a synthesis of classical teaching methods (definition through genus and species, Euler circles, the logical square) and recent international approaches (argument mapping, contextualization, integration with Explicable Artificial Intelligence), it proposes ways to overcome the aforementioned difficulties. One of the main conclusions of the work is the substantiation of the argument mapping method as an effective tool for visualizing the structure of reasoning and for bridging logical theory with the practice of analyzing real-world texts (political speeches, legal documents, journalism). The area of application of the research results encompasses the theory and practice of teaching logic, philosophy, critical thinking, and argumentation theory within the system of contemporary Russian higher education.

Annotation: The article describes the issue of evaluating the quality of texts generated by large language models when deployed locally in corporate information systems. The study focuses on analyzing the consistency between automatic evaluation metrics and expert assessment for short technical descriptions of data attributes. A medium-sized language model operating in a local computational environment with parameter optimization techniques was used as the research object. For the compiled dataset of generated texts, expert scores were obtained using a discrete rating scale, and automatic indicators reflecting semantic and lexical similarity to reference descriptions were calculated. Correlation analysis was performed, and a linear regression model was constructed to approximate expert evaluation based on automatic metric values. The results demonstrate that semantic metrics exhibit a high level of agreement with expert judgment and provide stable prediction of generation quality. The findings can be applied in automated validation and tuning of technical documentation generation systems.

Annotation: The article examines the future managers’ preparedness for career planning in conditions of high economic and social uncertainty. The study examines career components and the internal and external aspects of career de- velopment. It analyzes existing approaches to defining the concept of “career”, clarifying its content in light of professional activities under conditions of high uncertainty. This study demonstrates the role of self-management as a prerequisite for a successful managerial career and the extent to which psychological readiness components shape the future competitiveness of managers. The empirical study was based on a survey of students in the Management program. Analysis of the results revealed real difficulties in students’ career planning: low stress tolerance and a lack of habit in using psychological self-regulation techniques. The article proposes pathways for improving career planning skills among future managers based on psychological methods. It also provides recommendations for revising university educational programs to increase management students’ readiness to plan their professional careers in conditions of high uncertainty.

Annotation: The relevance of this study stems from the need to improve the accuracy and reproducibility of automated vertebral heart score (VHS) calculation in small companion animals. One of the key factors affecting the quality of anatomical structure segmentation is the low contrast of original radiographs, particularly in the regions of the thoracic vertebrae and the cardiac silhouette. This article proposes an adaptive digital image processing algorithm that combines local contrast enhancement, morphological extraction of bony structures, and nonlinear edge-preserving noise suppression. The algorithm is designed for use at two stages of the model lifecycle: during dataset preparation for expert annotation, and as a preprocessing step prior to inference of a trained computer vision model. The method description includes mathematical formalization of the components, justification for parameter selection, and the architecture of the algorithmic pipeline. Experimental validation of the developed algorithm’s effectiveness was conducted, including a comparison of annotation quality and the performance of models trained on original versus processed images.

Annotation: High-resolution electron microscopy (HREM) investigations of amorphous alloys generate extensive image datasets. However, the absence of a standardized data representation framework impedes interpretation, com- promises research reproducibility, and limits the reuse of experimental results. This study proposes a multi-level ontology model that formalizes the complete experimental workflow, encompassing microscope parameters, alloy characteristics, clustering outcomes, and atomic structure analysis. The model is described using applied logic language as formalism. The model comprises three interconnected levels that define the domain-specific terminology, the methods and their parameters required for processing experimental data, and the structure for representing information about specific experiments, associated image series, identified clusters, and atomic points. The modular, three-tiered architecture of ontology ensures extensibility, component reuse, and strict semantic integrity of data. The developed model forms the basis of a software complex supporting end-to-end processing and analysis of electron microscopy image data.